Monday, June 20, 2016

Males and females often differ in the average parasite loads
that they carry, and explanations for this pattern abound. For example, differences
in size, stress levels, hormones (see here),
exposure to parasites, and investment in defense have been shown to explain
variation in parasite loads between the sexes. Such sex-biased parasitism has
important implications for host behaviour and population dynamics, effects that
in turn can ripple through the community. Non-surprisingly then, sex-biased
parasitism is a recurrent topic in ecological parasitology; and yet, the
evolutionary consequences of sex-dependent variation in resistance - following changes
in parasite selection – are generally ignored.

At the same time as I was wondering about those evolutionary
consequences of sex-biased resistance, I found myself in a laboratory full of
guppies (Poecilia reticulata) coming from
a series of field introductions that I initially intended to use for exploring
female evolution of defense under relaxed selection (i.e. parasite removal – see
here). This seemed like an excellent opportunity first to use the males
that I was breeding in the lab, and second to have a go at the more general, and
understudied, subject of sex independent evolution. During the last two decades, awareness of the extent to which novel environments and changes in biotic
interactions may lead to rapid evolution has increased dramatically to the
point in which this is now a common consideration in basic ecological studies,
conservation efforts and management plans. Yet, one potential limitation of
most studies is that they either focus on one sex or conflate both sexes as if they
ought to experience the same level of selection and show the same response to
selection. In all fairness, such an assumption might be acceptable in some
instances, but should be carefully considered for sexually dimorphic traits or
when the potential for sex-biased selection exists. And, of course, one such
trait that may show such sex-independent responses to the same environmental
change is at the core of my research interests: defence against parasites.

The extent to which males and females might evolve
differently in response to the same environmental change is not straightforward,
and thus worthy of exploration. On one extreme of a continuum, we might expect
the sexes to show similar evolutionary responses given that they might
experience a similar environment and share most of their genetic background. On
the other extreme of the same continuum, we can expect the sexes to show
different responses given that they could experience the same environment in
different ways and differ in some important regions of their genome – as is
well documented for myriads of behavioural, morphological and physiological
sexually-dimorphic traits. Therefore, my collaborators and I decided to test
whether male and female guppies showing
sexually dimorphic resistance to a common and deleterious ectoparasite (Gyrodactylus turnbulli) evolved following
similar or divergent trajectories, after the experimental removal of said
parasite in four replicate populations (Dargent et
al. 2016).

First, we confirmed that resistance to Gyrodactylus differed between males and females from the (parasite-present)
ancestral population used to seed the (parasite-free) introductions. Indeed,
males had higher resistance than females, and this effect was not caused by
males being smaller in size – and thus providing less surface area for Gyrodactylus to grow – than females.
Second, as we showed previously (here),
we found that females in the four Gyrodactylus-released
introductions rapidly (4 and 8 generations) and repeatedly evolved increased resistance to the parasite. Interestingly,
males did not evolve increased or decreased resistance in those same four and
eight generations. Surprisingly, all four female populations shared the same
evolutionary trajectories in resistance trait-space (i.e. they evolved in
parallel) and towards the position of the ancestral male traits.

Although a potential argument could be that males evolve
much more slowly than females, this does not seem to be the case here; males
from these same populations have shown rapid evolution of other traits (e.g. colour
– see here).
Additionally, the explanations that we had outlined for female increased
evolution of resistance (here)
– that it was a pleitropic by-product of evolution in response to release from predation
- does not hold well for males. Males in the source population experience
stronger selection by predators than females, and therefore we would have expected
to see an even larger increase in resistance. Having no clear selective
explanations for the sex-specific evolution of resistance we consider the idea
of stronger evolutionary constrains in males than in females. Put simply, either
ancestral selection on resistance was stronger for males and depleted much of
the available genetic variance, and thus constrained further evolution, or
alternatively, the costs of increasing resistance are nonlinear making progress
towards ever higher resistance progressively more costly.

Studies of sex-biased parasitism recognize that behavioural
and physiological differences between the sexes can lead to divergent parasite
loads, and nonetheless, these studies ignore the potential effects of
sex-specific evolution on those traits that influence host infection levels.
Our results show that sex-biased resistance is a highly dynamic character, and
help clarify why it has been so challenging to establish general patterns and
mechanisms of sex-biased parasitism.

Thursday, June 16, 2016

Some time ago, I wrote a post called “High
Enthusiasm and Low R-Squared” in which I commented on how some research subjects
seem to garner interest far greater than their real importance to ecology and
evolution. One example I gave was genes of large effect, which are all the rage
in scientific tabloids yet probably contribute to only a minor fraction of
overall adaptation. Another example was biodiversity-ecosystem function
relationships, which often have low explanatory power. That is, for a given
biodiversity level, the range of ecosystem function is very large – even within
a single experiment. A third example was parallel (or convergent) evolution,
where instead most adaptation seems to be non-parallel (and non-convergent).

From my forthcoming book "Eco-Evolutionary Dynamics"

The fourth example I gave was so called “behavioral types”
or “personalities” (and the related idea of behavioral “syndromes”), for which
I argued that – in reality – behavior at any one time (or context) is usually not
very predictive of behavior at another time or context. I didn’t mean to
suggest that behavioral types weren’t interesting and, in fact, my former
postdoc Lisa Jacquin just published in the Journal
of Evolutionary Biology our cool study of how behavioral types evolve in
Trinidadian guppies in response to different
predation and parasitism regimes. (Although a reviewer made us excise most
mentions of “personality” from the MS.) Rather, the point of my original post
was simply that behavioral types might be overblown with regard how much research
emphasis was placed on them.

I am currently toward the end of a two-week trip to Europe
that included stops in southern Switzerland, Zurich, Berlin, and Leuven
(Belgium). After the first stop, which was for a conference/workshop on the “Genomic
basis of eco-evolutionary dynamics,” I wrote a post that revised my original
criticism of one of the above areas – genes of large effect. While I remain
confident that most adaptation is the result of genes of small-to-modest
effect, I am now also interested in the possibility that some specific genes
might have reasonably large effects on eco-evolutionary dynamics. We might call
them “keystone genes” in echo of Bob Paine’s keystone species idea. (Sadly Bob recently
passed away.)

My second visit on the trip was to the IGB (Leibniz
Institute of Freshwater Ecology and Inland Fisheries), where I was hosted by
Robert Arlinghaus. A series of discussions on that visit have motivated me to
revisit another of my suggested areas of “high enthusiasm and low r-squared.” A
number of people at the IGB study behavioral types and some also examine the
influence of those types on ecological processes. Yet- to expand my earlier
criticism – behavioral types might not have much influence on ecological processes
because behavior is quite variable to begin with (i.e., “types” are not really that
consistent) and individual-level behavior might or might not have much
influence on ecological function. To
address these concerns we need to calculate the effect size of behavioral types,
ideally in relation to how the same ecological parameter is influenced by some
other causal force that we already know is important. So what we need is an
experiment that asks about the effect size of behavioral types in relation to other
drivers of ecological function – and why not “ecotypes”?

Ecotypes are, classically, populations adapted to particular
environments, such as benthic versus limnetic feeding environments for fishes,
different soil types for plants, high-predation versus low-predation
environments, and so on. A lot of work on fish (whitefish, stickleback,
guppies, alewives) has shown that these ecotypes differ in their influence on
various community and ecosystem level ecological processes. So why not
implement an experiment explicitly comparing the ecological influence of different
ecotypes (e.g., fish obtained from populations adapted to different
environments) to the ecological influence of different behavioral types (e.g.,
fish within those populations that are either bold or shy). Although this
particular comparison would certainly be interesting, it is unfair in one respect.
The “ecotype” effect is between populations, where evolutionary divergence is
possible, whereas the behavioral type effect is within populations, where
evolutionary divergence is more difficult.

The ecological effects of some fish ecotypes - also from my book.

Fortunately, we do have a “fair” and appropriate comparison to
make. In addition to situations where benthic versus limnetic ecotypes are
separate populations, such as in different lakes and sometimes even within
lakes, many fish populations also show continuous quantitative variation among
individuals along a continuum from limnetic to benthic. That is, within any
given population in a given lake, some individuals will be specialized for
limnetic feeding and others for benthic feeding. Using such a population, one
could perform a mesocosm common “gardening” experiment crossing behavioral type
(presumably assayed before the experiment) with ecotype (perhaps based on
capture location – inshore versus offshore – or on characteristic morphology or
coloration). One could then assess the relative importance of these two factors
for the usual ecological parameters, such as zooplankton abundance, water
clarity, DOC, benthic invertebrate communities, decomposition rates, and so on.

Beyond the just-noted benefit of allowing a direct
comparison between the effects of behavioral type and ecotype, this experiment
has another advantage – it can consider interactions between the two levels of
variation. For instance, the effects of a given behavioral type (e.g., bold or
shy) might be evident only for a particular ecotype, and so an experiment
crossing the two levels of variation has the potential to increase one’s ability
to detect the effects of either. Of course, the effect of a given behavioral type
or ecotype on ecological variables likely also depends on the testing
environment: bold versus shy might only matter for benthic fish in benthic
environments. So one would ideally cross behavioral type with ecotype with
testing environment in a fully crossed design. In addition, if one is to make
general statements about the effects of ecotype or behavioral type, one would
want to do the experiment for at least two independent populations – that is,
testing the parallelism across evolutionary replicates of interactions between
behavioral type, ecotype, and testing environment shaping ecological function. Yes,
I realize this is a massive undertaking but I think we should at least consider
the ideal experiment before then chopping it down to a more manageable subset.

Behavioral types and ecotypes might be correlated within
populations (benthic fish might be more shy) and so separating the two effects
might be difficult. Yet it remains critical. Imagine that behavioral types are
closely correlated with ecotypes, such as when foraging environment or predator
environment leads to the evolution of different behavior types – or vice versa.
In such cases, an experiment focusing on only one or the other axis of
variation would be unable to determine the true causality – because the two
axes (behavioral type and ecotype) are closely correlated. That is, the apparent
differences in ecological effects between two behavioral types might arise
simply because behavioral type is correlated with (other) aspects of ecotype –
and those other aspects are what drives the ecological effects. In this case,
behavioral type is not the causal factor despite appearing so in the
experiment. Thus, it seems most profitable to first examine the association
between behavioral type and ecotype (within and among populations) and then –
through careful selection of individuals that break the mold – that is, that cross
the two factors to the extent possible.

I hope that this post will inspire someone toward such an
experiment. If behavioral types prove to be as important as ecotypes for
eco-evolutionary dynamics, then I will happily extol their virtues in all
future attempts opportunities. More generally, an experiment such as that
suggested here would help show other evolutionary biologists and ecologists
that the study of behavioral types is important for our understanding of
eco-evolutionary dynamics.

Saturday, June 11, 2016

(The title of this post is new as of June 15, 2016, in honor of Bob Paine, who just passed away.)While writing my book on Eco-Evolutionary Dymamics, I wanted
a chapter on the genetic/genomic underpinnings of the interactions between ecology
and evolution. About the time I finished the chapter, I received an invitation
to submit a paper to Heredity, and so I converted the book chapter into a paper (Hendry 2013).

In the paper, I suggested that “The genetics and genomics of
eco-evolutionary dynamics will be – to a large extent – the genetics and
genomics of phenotypic traits” (more about this below) and then concluded (from
the abstract):

(1)
Considerable additive genetic variance is present for most traits in most
populations.

(2)
Trait correlations do not consistently oppose selection.

(3)
Adaptive differences between populations often involve dominance and epistasis.

(4)
Most adaptation is the result of genes of small-to-modest effect,

although
(5) some genes certainly have larger effects than the others.

(6)
Adaptation by independent lineages to similar environments is mostly driven by
different alleles/genes.

(7)
Adaptation to new environments is mostly driven by standing genetic variation,
although new mutations can be important in some instances.

(8)
Adaptation is driven by both structural and regulatory genetic variation, with
recent studies emphasizing the latter.

(9)
The ecological effects of organisms, considered as extended phenotypes, are
often heritable.

Research in the past three years seems only to have
bolstered these conclusions, but I can now see some important nuances.

Last week, I was at Monte Verita in Ascona, southern
Switzerland, for a meeting titled The Genetics and Genomics of Eco-Evolutionary
Dynamics, organized by a number of postdocs at the Adaptation to a Changing
Environment (ACE) centre . The meeting brought together people studying the
genomics of adaptation and people studying eco-evolutionary dynamics (two
largely non-overlapping groups) to see if some progress could be made toward integrating
the two areas of research.

The last light of day from my room at Monte Verita, Ascona, Switzerland.

For some time, it wasn’t clear that such integration was
possible or profitable. In particular, because all eco-evolutionary dynamics
are driven by phenotypes, the genomics of eco-evolutionary dynamics should
simply be the genomics of phenotypic traits – a point that I argued in my 2013
paper (as noted above). However, a problem arises in the case of
eco-evolutionary dynamics because the correlation between genes (i.e., genetic
variation and evolutionary change) and ecological function is expected to be
product of two correlations: that between genes and traits and that between
traits and ecological function. Given that correlations are between 0 and 1,
this product should be weaker than either of the two correlations. We already
know from many studies that each of these two correlations is relative weak,
probably nearly always less than 0.5, and so the correlation between genes and
ecological function should be VERY weak. In short, the initial perspective of
the group was that the genetics and genomics of eco-evolutionary dynamics would
be considerably more difficult to study than the genetics and genomics of
phenotypic traits (which is already quite hard).

This prospect made most of the genomics people in the room
rather less than excited as it seemed to suggest that genomic mapping of
ecological function – and the search for candidate genes and causal variants –
would be hopeless. This same skepticism was – to some extent – the point I made
in my 2013 paper where I argued that the genomics of eco-evolutionary dynamics
would be very polygenic and so better served by quantitative genetics. However,
further discussion brought up several important points that suggest the tools
of genomics might be profitably turned to the exploration of ecological
function.

These points can be illustrated by reference to a path model,
where a set of genes influence a set of traits which influence a set of
ecological functions. In these models, the correlations along each casual
pathway are multiplied to get the final correlation between the start (a gene)
and end (an ecological function) of that pathway as noted above. However, when
multiple pathways link genes and ecological functions, those final correlations
are summed across the pathways to get the total effect. Thinking in this manner
yields several insights:

1. The effects of a given gene on a given ecological function
could be greater than the effects of that gene on any one phenotypic trait.
This situation could arise when one gene influences multiple traits that each
influence the same ecological function. It could also arise if a given gene
influences both a trait with a key ecological function and also organismal
fitness, with fitness then also influencing ecological function. And the
situation is even more promising if more than one aspect of ecological function
is influenced by traits and (most obviously) by organismal fitness, such that
the total ecological effect could be considerably greater than any single
ecological effect.

2. The total effect of all genes on a given ecological
function (or on total ecological function) could be large if multiple genes
influence one trait that has a strong effect on ecological function(s) or if multiple
genes influence multiple traits that together to have large effects on
ecological function(s). Further, if we consider a multi-species context, a
given ecological function could be influenced by genetic variation in multiple species
– and so the total genetic effects of all species on a given ecological
function could be large. This last possibility suggests the potential value of analyzing
GxG effects on ecological function – as has already been done in several
studies where the Gs are different clones. Of particular interest, GxG
interactions suggest that the effects of genes in a given species might be most
easily revealed if they are assessed on several genomic backgrounds of the
other interacting species.

Seth Rudman gives a summary of the working group. If you look closely, you can see a scribbled version of the path model on the board at left.

If I had the chance, I would now modify the statements in my
2013 paper to make the above points. I would then reiterate that we can treat
the ecological effects of individuals as extended phenotypes, and so attempt
all of the same genomic work done for more traditional traits (and sometimes
fitness): QTL mapping, genome scans (comparing groups of individuals with
different ecological functions), genome-wide association studies, candidate
gene discovery, and searches causal variants (depending on the specific points
of interest). Of course, these methods will need to be combined with
quantitative genetic analyses, given that much ecological function will surely
be polygenic.

Sadly, I can’t modify the 2013 paper. Nor can I modify the
corresponding book chapter given that I will receive the proofs tomorrow and
the publisher won’t want me making large changes. However, you can stay tuned
for the paper resulting from the discussions in Switzerland, which is being led
by Seth Rudman. Go Seth go!

The Genomics of Eco-Evolutionary Dynamics group.

A few days after writing this post, Bob Paine, the originator of the keystone species concept passed away. I took a class from Bob Paine when I was a graduate student and have certainly referred to keystone species multiple times in my writing. In particular, I have argued that eco-evolutionary dynamics are most likely when the evolving focal species is a keystone species (or a foundation species or a ecosystem engineer and so on). Thus, if we are to search for particular genes of large effect, we would probably want to look in these species. And we might then call these large ecological effect genes "keystone genes."